This summer marked the fifth year of the OpenDP Interns and Fellows Program! We received a record number of applications this year, and in June we welcomed three interns and two fellows. Our internship program offers a summer of research and mentorship for students interested in implementing differential privacy. Guided by OpenDP’s vision, we match…
You’ll find new features in the 0.13 release and an update for DP Wizard in the details below. The OpenDP library and DP Wizard are improved with your feedback and contributions, so please check out these tools and let us know what you think via our slack channel or emailing us directly at info@opendp.org!…
The Differential Privacy Beyond Algorithms Workshop took place at the OpenDP Community Meeting with the goal to bring together participants thinking about aspects of DP deployments beyond algorithms and technical tools. Read the full recap in the blog and get involved in the community!…
The UNHCR, the United Nations Refugee Agency, reached out to OpenDP looking to hire a consultant for 6 months to test the OpenDP libraries with their microdata. Read more about the project and challenges due to the particular structure of humanitarian data and how Nitin Kohli (UC Berkeley) found success experimenting with a new approach of using existing OpenDP libraries….
We are excited to spotlight the work of Simson Garfinkel and announce his upcoming book, Differential Privacy! Simson researches and writes at the intersection of AI, privacy, and digital forensics….
In this post, we will show a simple tutorial describing the process of adding differential privacy to the United States Broadband Usage Percentages Dataset. The tutorial will go through all steps of a data release project, from defining all data aggregations and computations in a non-private setting and identifying the points in the pipeline where data transformations, such as clamping, are necessary, all the way to implementing the data pipeline with the appropriate differential privacy mechanism using OpenDP….
The OpenDP team is excited to bring you our latest release, OpenDP Library 0.12! The OpenDP Library is a modular collection of algorithms for building privacy-preserving applications, with an extensible approach to tracking privacy, and a vetted implementation. It is available as binaries for Python on PyPI, for R on R-universe, for Rust on crates.io, or in source…
We are pleased to announce the 2025 OpenDP Interns and Visiting Fellows call for applications! Starting today, we are seeking interested individuals that are interested in contributing to and helping grow the OpenDP library and community. OpenDP Interns are typically undergraduate, post-bacc, or graduate students but those at other stages are welcome to apply. It is preferred…
OpenDP is pleased to announce the first release of DP Wizard, an interactive tool to explore the effect of different parameter choices, and an assistant for implementing those choices with the OpenDP library. DP Wizard builds on what we’ve learned from DP Creator, but offers a simplified development and install process and a streamlined workflow. We would…
A recent publication of a comprehensive technical report marking the completion of Phase 1 of the Christchurch Call Initiative on Algorithmic Outcomes (CCIAO) was announced last month which highlights advancements in AI Auditing and safety, allowing external researchers to conduct privacy-preserving audits of production recommender algorithms at LinkedIn and Daily Motion using PySyft and OpenDP….
